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Friday, April 12, 2019

Boom time for edge AI hardware

By Nick Flaherty www.flaherty.co.uk

The Edge AI Hardware Market is expected to see shipment of 610 million units this year and is likely to reach 1559.3 million units by 2024, at a CAGR of 20.64 percent.

The report "Edge AI Hardware Market by Device (Smartphones, Cameras, Robots, Automobile, Smart Speakers, Wearables, and Smart Mirror), Processor (CPU, GPU, ASIC and Others), Power Consumption, Process, End User Industry, and Region - Global Forecast to 2024" from MarketsandMarkets sees major drivers for the market's growth are growing demand for low latency and real-time processing on edge devices and emergence of AI co-processors for edge computing. 

The underlying opportunities for the edge AI hardware market include growing demand for edge computing in IoT and dedicated AI processors for on-device image analytics. Major restraints for the market are limited on-device training and limited number of AI experts. Power consumption and size constraint also pose major challenges to the edge AI hardware market.

In terms of device type, cameras are expected to have the highest growth as an integral part of various smart devices with Wi-Fi support, smart functions, superior speed, and enhanced performance for years. However, cameras as standalone smart devices with vision processing units (VPU) that help deliver power-efficient solutions for vision and artificial intelligence are now entering the market. 

Such devices are designed to run deep neural networks at high speed and low power without compromising on accuracy, which enables devices to see, understand, and respond to their environment in real time. The VPU market is constantly witnessing advancements. For instance, the previous-generation Myriad 2 VPU developed by Movidius offered deep neural network support at relatively low power. 

The new Myriad X VPU introduced by Intel can achieve roughly 10X better performance; with multiple neural networks running simultaneously, to offer extended autonomous capabilities across wide range of applications such as drones, robotics, VR, and smart cameras. Due to developments like these, the market is witnessing an influx of cameras powered by AI chips that allow these devices to judge moment's best suited to capture stills or videos.

Dedicated AI chip or AI processors were one of the major developments in the smartphone technology last year. Increasing demand for real-time speech and voice recognition and analysis, as well as technical advancements in smartphone image recognition is driving the market for AI processors in smartphones. 

A majority of AI processors have an additional inbuilt Neural Processing Unit (NPU) that can handle significant amounts of parallel processing, uses low power, and is capable of cognitive tasks. With AI processors built in a phone, these AI tasks could be carried out right on the device, even without any connectivity; this would not only improve performance of the device, but also reduce strain on the battery. 

China is the largest market for the technology. The country is undertaking many projects, especially in the infrastructure sector, such as rail, airport, stadiums, and highway systems that are expected to require high-definition surveillance systems, which can capture clear images even in darkness. 

China is home to video surveillance players such as Dahua and Hikvision that dominate the video surveillance hardware market. Both companies have already launched deep learning surveillance cameras in the market and China has already started deploying cloud AI based surveillance cameras to monitor its citizens. This development will lead to adoption of edge AI in surveillance cameras. 


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